A parallel unidirectional coupled DEM-PBM model for the efficient simulation of computationally intensive particulate process systems

Chaitanya Sampat, Franklin Bettencourt, Yukteshwar Baranwal, Ioannis Paraskevakos, Anik Chaturbedi, Subhodh Karkala, Shantenu Jha, Rohit Ramachandran, Marianthi Ierapetritou

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The accurate modeling of the physics underlying particulate processes is complicated and requires significant computational capabilities to solve using particle-based models. In this work, a unidirectional multi-scale approach was used to model the high shear wet granulation process. A multi-dimensional population balance model (PBM) was developed with a mechanistic kernel, which in turn obtained collision data from the discrete element modeling (DEM) simulation. The PBM was parallelized using a hybrid OpenMP+MPI approach. The DEM simulations were performed using LIGGGHTS, which was parallelized using MPI. Speedups of approximately 14 were obtained for the PBM simulations and approximately 12 for the DEM simulations. The uni-directional coupling of DEM to PBM was performed using middle-ware components (RADICAL-Pilot) that did not require modifications of the DEM or PBM codes, yet supported flexible execution on high-performance platforms. Results demonstrate scaling from 1 to 128 cores for the PBM and up to 256 cores for the DEM. The proposed method, implementations and middle-ware enable the modeling of high shear wet granulation process faster than existing approaches in literature.

Original languageEnglish (US)
Pages (from-to)128-142
Number of pages15
JournalComputers and Chemical Engineering
Volume119
DOIs
StatePublished - Nov 2 2018

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications

Keywords

  • Discrete element method
  • Granulation
  • MPI and OpenMP
  • Pharmaceutical process design
  • Population balance model

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